Cytotoxicity and fibroblast properties during in vitro test of biphasic calcium phosphate/poly-dl-lactide-co-glycolide biocomposites and different phosphate materials

Reconstruction of bone defects is one of the major therapeutic goals in various clinical fields. Bone replacement materials must satisfy a number of criteria. Biological criteria are biocompatibility, controlled biodegradability, and osteoconductive or even osteogenic potential. The material should have a three-dimensional structure with an interconnected pore system so as to permit cell growth and transport of substances. The surface must permit cell adhesion and proliferation. Composite biomaterials have enormous potential for natural bone tissue reparation, filling and augmentation. Calcium hydroxyapatite/polymer composite biomaterials belong to this group of composites and, because of their osteoconductive and biocompatible properties, can be successfully implemented within bone tissue reparations. In this study, possible differences between BCP/DLPLG, pure BCP, and Bio-Oss materials were examined in vitro. During overnight incubations, fibroblast and fibroblast-like cells (L929, MRC5) were able to adhere, spread, and remain viable on BCP, BCP/PLGA, and Bio-Oss discs, as was evidenced by using light- and LVSEM-microscopy. Inhibiting influence over the cell growth is more pronounced in the cases of BCP usage on both cell lines--41.29% for L929 and 43.08% for MRC-5 cells. MRC-5 cells are, within the given experimental conditions, less sensitive on inhibiting effects for the materials BCP/PLGA and Bio-Oss (10.13% and 10.76%, respectively) than for the L929 cell lines (23.02% and 15.44%, respectively).     

Fiber-based polarization-sensitive Mueller matrix optical coherence tomography with continuous source polarization modulation

We report on a new configuration of fiber-based polarization-sensitive Mueller matrix optical coherence tomography that permits the acquisition of the round-trip Jones matrix of a biological sample using only one light source and a single depth scan. In this new configuration, a polarization modulator is used in the source arm to continuously modulate the incident polarization state for both the reference and the sample arms. The Jones matrix of the sample can be calculated from the two frequency terms in the two detection channels. The first term is modulated by the carrier frequency, which is determined by the longitudinal scanning mechanism, whereas the other term is modulated by the beat frequency between the carrier frequency and the second harmonic of the modulation frequency of the polarization modulator. One important feature of this system is that, for the first time to our knowledge, the Jones matrix of the sample can be calculated with a single detection channel and a single measurement when diattenuation is negligible. The system was successfully tested by imaging both standard polarization elements and biological samples.     

Energy efficiency on location based applications in mobile cloud computing: a survey

The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions.     

Fuzzy model-based optimal energy control during the electrical discharge machining

Neural Computing and Applications - This research aimed to describe a fuzzy optimal energy control strategy, so the electrical discharge machining (EDM) process can be optimized as a whole. The...     

Diabetes Prediction Algorithm Using Recursive Ridge Regression L2

At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a predictive model with high accuracy. In this work, a wrapper-based feature selection method called recursive feature elimination is combined with ridge regression (L2) to form a hybrid L2 regulated feature selection algorithm for overcoming the overfitting problem of data set. Overfitting is a major problem in feature selection, where the new data are unfit to the model because the training data are small. Ridge regression is mainly used to overcome the overfitting problem. The features are selected by using the proposed feature selection method, and random forest classifier is used to classify the data on the basis of the selected features. This work uses the Pima Indians Diabetes data set, and the evaluated results are compared with the existing algorithms to prove the accuracy of the proposed algorithm. The accuracy of the proposed algorithm in predicting diabetes is 100%, and its area under the curve is 97%. The proposed algorithm outperforms existing algorithms.     

Benchtop Fluorination of Fluorescent Nanodiamonds on a Preparative Scale: Toward Unusually Hydrophilic Bright Particles

Fluorination of diamonds modulates their optical and electromagnetic properties and creates surfaces with increased hydrophobicity. In addition, fluorination of diamonds and nanodiamonds has been recently shown to stabilize fluorescent nitrogen‐vacancy centers, which can serve as extremely sensitive single atomic defects in a vast range of sensing applications from quantum physics to high‐resolution biological imaging. Traditionally, fluorination of carbon nanomaterials has been achieved using harsh and complex experimental conditions, creating hydrophobic interfaces with difficult dispersibility in aqueous environments. Here, a mild benchtop approach to nanodiamond fluorination is described using selective Ag⁺‐catalyzed radical substitution of surface carboxyls for fluorine. In contrast to other approaches, this high‐yielding procedure does not etch diamond carbons and produces a highly hydrophilic interface with mixed C?F and C?OH termination. This dual functionalization of nanodiamonds suppresses detrimental hydrophobic interactions that would lead to colloidal destabilization of nanodiamonds. It is also demonstrated that even a relatively low surface density of fluorine contributes to stabilization of negatively charged nitrogen‐vacancy centers and boosts their fluorescence. The simultaneous control of the surface hydrophilicity and the fluorescence of nitrogen‐vacancy centers is an important issue enabling direct application of fluorescent nanodiamonds as nanosensors for quantum optical and magnetometry measurements operated in biological environment.     

Structural changes during 3D printing of bioderived and synthetic thermoplastic materials

Three-dimensional (3D) printing processes are nowadays leading the charge in transforming traditional art, engineering, and manufacturing processes. In this study, the structural and thermal behavior of commercially available filaments composed of synthetic poly(acrylonitrile-co-butadiene-co-styrene) thermoplastic as well as poly(lactic acid) and poly(lactic acid)/polyhydroxyalcanoate reinforced with bamboo (Bambusa sp.) wood flour composite biothermoplastics were assessed by differential scanning calorimetry and infrared spectroscopy, aiming to understand the modifications that occur at the molecular level during their 3D printing. It has been determined that the biothermoplastic materials undergo both molecular reorientations related to tacticity increase and crystallinity decrease when submitted to 3D printing extrusion, while the synthetic thermoplastic undergoes crosslinking due to its butadiene component. All of the studied materials present good water stability (with water uptake values between 0.8% and 24%), and the water absorption follows a pseudo-Fickian mechanism. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 .     

Studies in structural characterization of silica–heteropolyacids composites prepared by sol–gel method

Heteropolyacids (HPAs) which are included in mesoporous silica, H₃PMo₁₂O₄₀/SiO₂ and H₄PMo₁₁VO₄₀/SiO₂ have been synthesized by a sol–gel technique that involves hydrolysis of ethyl orthosilicate. The effect of incorporation of heteropolyacids species on silica matrix was studied by powder X-ray diffraction (XRD), Fourier transform infrared (FT-IR) and Raman spectroscopy, thermo gravimetric analysis (TGA) and differential thermal analysis (DTA), N₂ adsorption–desorption, scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS).